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    },
    {
     "name": "stdout",
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      "1095 1177 1425 1766\n",
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     ]
    }
   ],
   "source": [
    "import cv2\n",
    "import os\n",
    "from matplotlib import pyplot as plt\n",
    "from xml.etree.ElementTree import parse\n",
    "from xml.etree.ElementTree import Element, dump\n",
    "import xml.etree.ElementTree as ET\n",
    "\n",
    "\n",
    "filename_list=os.listdir(\"train_data/pill_result/xml\")\n",
    "filename_list.sort()\n",
    "for file_name in filename_list:\n",
    "    img_filename=file_name.split(\".\")[0]\n",
    "    if len(img_filename) < 2:\n",
    "        continue\n",
    "    img = cv2.imread(\"train_data/pill_box/gray_img/\"+img_filename+\".jpg\"); ######자를 이미지\n",
    "    \n",
    "    doc = ET.parse(\"train_data/pill_box/xml/\"+file_name)\n",
    "    root = doc.getroot()\n",
    "    object_tag = root.findall(\"object\") #pill\n",
    "    \n",
    "    obj=object_tag[0]\n",
    "    box_tag_pill = obj.find(\"bndbox\")\n",
    "    xmin_pill = box_tag_pill.findtext(\"xmin\")\n",
    "    ymin_pill = box_tag_pill.findtext(\"ymin\")\n",
    "    xmax_pill = box_tag_pill.findtext(\"xmax\")\n",
    "    ymax_pill = box_tag_pill.findtext(\"ymax\")\n",
    "    print(\"-\"*50)\n",
    "    print(xmin_pill, ymin_pill, xmax_pill,ymax_pill) \n",
    "    print(\"Save!: \"+\"train_data/pill_result/img/\"+img_filename+\".jpg\")\n",
    "    try: #.jpg,.JPG가 달라지면 error가 나기때문에 try, except문 사용\n",
    "        cv2.imwrite(\"train_data/pill_result/img/\"+img_filename+\".jpg\",img[int(ymin_pill):int(ymax_pill),int(xmin_pill):int(xmax_pill)])\n",
    "    except:\n",
    "        img = cv2.imread(\"train_data/pill_box/gray_img/\"+img_filename+\".JPG\"); ######자를 이미지\n",
    "        cv2.imwrite(\"train_data/pill_result/img/\"+img_filename+\".JPG\",img[int(ymin_pill):int(ymax_pill),int(xmin_pill):int(xmax_pill)])\n",
    "    \n",
    "    \n",
    "    #print(\"Save!: \"+\"train_data/pill_result/img/\"+file_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".ipynb_checkpoints\n",
      "11_B_1_R_D_1.jpg\n",
      "11_B_1_R_D_2.jpg\n",
      "11_B_1_R_L_1.jpg\n",
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      "11_B_1_W_D_1.jpg\n",
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      "11_B_1_W_L_1.jpg\n",
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      "11_B_2_R_D_1.jpg\n",
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      "9_F_2_W_L_2.jpg\n"
     ]
    }
   ],
   "source": [
    "import cv2\n",
    "import os\n",
    "from matplotlib import pyplot as plt\n",
    "from xml.etree.ElementTree import parse\n",
    "from xml.etree.ElementTree import Element, dump\n",
    "import xml.etree.ElementTree as ET\n",
    "\n",
    "\n",
    "filename_list=os.listdir(\"train_data/pill_box/gray_img/\")\n",
    "filename_list.sort()\n",
    "for file_name in filename_list:\n",
    "    print(file_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
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    "version": 3
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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